Hi,
I’m using part 2, lesson 8 basics to try to train a model that can recognize upper-body joints in images. My dataset are from the FLIC dataset with annotated joints (both wrists, both elbows, both shoulders, and head, for a total of 14 values (7 x/y coordinates). My CSV consists of the filename and a space-seperated list of the coordinates ( in y/x format, although I’ve also tried x/y format with same results).
Everything works great when I follow exactly the bounding-box example to augment the bounding-box data set, but when I try to augment the joints data set, I get IndexError when on the line x, y = next( iter( md.aug_dl ). Without augmentation, it seems to work fine.
f_model = resnet34
sz = 224
bs = 64
augs = [RandomFlip(tfm_y=TfmType.COORD),
RandomRotate(30, tfm_y=TfmType.COORD),
RandomLighting(0.1,0.1, tfm_y=TfmType.COORD)]
tfms = tfms_from_model(f_model, sz, crop_type=CropType.NO, tfm_y=TfmType.COORD, aug_tfms=augs)
md = ImageClassifierData.from_csv(dataPath, imagePath, newTrainCsvPath, tfms=tfms, continuous=True, bs=4)
def show_img( im, figsize = None, ax = None ):
if not ax: fig, ax = plt.subplots( figsize = figsize )
ax.imshow( im )
ax.get_xaxis().set_visible( False )
ax.get_yaxis().set_visible( False )
return ax
idx = 3
fig, axes = plt.subplots(3, 3, figsize = (9, 9))
for i, ax in enumerate( axes.flat ):
x, y= next(iter(md.aug_dl)) # <--- IndexError here
#ima = md.val_ds.denorm( to_np( x ))[idx]
#b = to_np( y[idx] )
##print( y[idx] )
#print( b )
#show_img( ima, ax=ax)
#plot_joints( ax, b )
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-13-ccf9064a3abb> in <module>
2 fig, axes = plt.subplots(3, 3, figsize = (9, 9))
3 for i, ax in enumerate( axes.flat ):
----> 4 x, y= next(iter(md.aug_dl))
5 #ima = md.val_ds.denorm( to_np( x ))[idx]
6 #b = to_np( y[idx] )
~/fastai/courses/dl2/fastai/dataloader.py in __iter__(self)
86 # avoid py3.6 issue where queue is infinite and can result in memory exhaustion
87 for c in chunk_iter(iter(self.batch_sampler), self.num_workers*10):
---> 88 for batch in e.map(self.get_batch, c):
89 yield get_tensor(batch, self.pin_memory, self.half)
90
~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result_iterator()
584 # Careful not to keep a reference to the popped future
585 if timeout is None:
--> 586 yield fs.pop().result()
587 else:
588 yield fs.pop().result(end_time - time.time())
~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
430 raise CancelledError()
431 elif self._state == FINISHED:
--> 432 return self.__get_result()
433 else:
434 raise TimeoutError()
~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/thread.py in run(self)
54
55 try:
---> 56 result = self.fn(*self.args, **self.kwargs)
57 except BaseException as exc:
58 self.future.set_exception(exc)
~/fastai/courses/dl2/fastai/dataloader.py in get_batch(self, indices)
73
74 def get_batch(self, indices):
---> 75 res = self.np_collate([self.dataset[i] for i in indices])
76 if self.transpose: res[0] = res[0].T
77 if self.transpose_y: res[1] = res[1].T
~/fastai/courses/dl2/fastai/dataloader.py in <listcomp>(.0)
73
74 def get_batch(self, indices):
---> 75 res = self.np_collate([self.dataset[i] for i in indices])
76 if self.transpose: res[0] = res[0].T
77 if self.transpose_y: res[1] = res[1].T
~/fastai/courses/dl2/fastai/dataset.py in __getitem__(self, idx)
201 xs,ys = zip(*[self.get1item(i) for i in range(*idx.indices(self.n))])
202 return np.stack(xs),ys
--> 203 return self.get1item(idx)
204
205 def __len__(self): return self.n
~/fastai/courses/dl2/fastai/dataset.py in get1item(self, idx)
195 def get1item(self, idx):
196 x,y = self.get_x(idx),self.get_y(idx)
--> 197 return self.get(self.transform, x, y)
198
199 def __getitem__(self, idx):
~/fastai/courses/dl2/fastai/dataset.py in get(self, tfm, x, y)
206
207 def get(self, tfm, x, y):
--> 208 return (x,y) if tfm is None else tfm(x,y)
209
210 @abstractmethod
~/fastai/courses/dl2/fastai/transforms.py in __call__(self, im, y)
646 self.tfms.append(ChannelOrder(tfm_y))
647
--> 648 def __call__(self, im, y=None): return compose(im, y, self.tfms)
649 def __repr__(self): return str(self.tfms)
650
~/fastai/courses/dl2/fastai/transforms.py in compose(im, y, fns)
621 for fn in fns:
622 #pdb.set_trace()
--> 623 im, y =fn(im, y)
624 return im if y is None else (im, y)
625
~/fastai/courses/dl2/fastai/transforms.py in __call__(self, x, y)
233 x,y = ((self.transform(x),y) if self.tfm_y==TfmType.NO
234 else self.transform(x,y) if self.tfm_y in (TfmType.PIXEL, TfmType.CLASS)
--> 235 else self.transform_coord(x,y))
236 return x, y
237
~/fastai/courses/dl2/fastai/transforms.py in transform_coord(self, x, ys)
264 def transform_coord(self, x, ys):
265 yp = partition(ys, 4)
--> 266 y2 = [self.map_y(y,x) for y in yp]
267 x = self.do_transform(x, False)
268 return x, np.concatenate(y2)
~/fastai/courses/dl2/fastai/transforms.py in <listcomp>(.0)
264 def transform_coord(self, x, ys):
265 yp = partition(ys, 4)
--> 266 y2 = [self.map_y(y,x) for y in yp]
267 x = self.do_transform(x, False)
268 return x, np.concatenate(y2)
~/fastai/courses/dl2/fastai/transforms.py in map_y(self, y0, x)
258
259 def map_y(self, y0, x):
--> 260 y = CoordTransform.make_square(y0, x)
261 y_tr = self.do_transform(y, True)
262 return to_bb(y_tr)
~/fastai/courses/dl2/fastai/transforms.py in make_square(y, x)
254 y1 = np.zeros((r, c))
255 y = y.astype(np.int)
--> 256 y1[y[0]:y[2], y[1]:y[3]] = 1.
257 return y1
258
IndexError: index 2 is out of bounds for axis 0 with size 2
And a subset of the CSV:
['fileName,joints\n',
'12-oclock-high-special-edition-00004221.jpg,415.0625 225.9918213 368.6132813 244.13876340000002 261.578125 223.9754944 161.94791669999998 254.22039790000002 251.4804688 123.1591797 376.6914063 80.81632233 423.140625 175.5836639\n',
'12-oclock-high-special-edition-00004281.jpg,372.421875 301.51019289999994 333.6796875 303.657135 223.9101563 258.5714417 153.6002604 243.5428569 234.671875 129.7550964 387.4882813 88.96327209 406.859375 192.0163269\n',
'12-oclock-high-special-edition-00006331.jpg,278.125 351.9591675 249.125 328.39999389999997 189.3125 324.7755127 141.58333330000002 303.63265989999996 189.3125 235.97550959999998 270.875 225.1020355 307.125 266.7836914\n',
'12-oclock-high-special-edition-00006361.jpg,322.453125 367.4693909 294.671875 331.836731 213.3125 327.87756349999995 155.10416669999998 297.5238139 197.4375 195.2449036 276.8125 175.4489746 338.328125 165.5510254\n']
Any help would be appreciated!